no code implementations • 20 Jun 2021 • Manmeet Singh, Bipin Kumar, Suryachandra Rao, Sukhpal Singh Gill, Rajib Chattopadhyay, Ravi S Nanjundiah, Dev Niyogi
This study is a proof-of-concept showing that residual learning-based UNET can unravel physical relationships to target precipitation, and those physical constraints can be used in the dynamical operational models towards improved precipitation forecasts.
